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- Tasks: Build and deploy cutting-edge AI models to solve complex problems.
- Company: Well-funded AI startup with a team of top-tier talent.
- Benefits: Competitive salary up to £300k, significant equity, and a dynamic work environment.
- Why this job: Tackle unsolved challenges in AI while collaborating with elite engineers.
- Qualifications: 5+ years in AI/ML engineering, strong Python skills, and production experience.
- Other info: In-office role in London with excellent career growth opportunities.
Our client is a very well-funded AI startup solving some of the hardest problems in production large language models. They are building systems that reliably handle complex, multi-step reasoning tasks at massive scale.
Their team combines talent from top-tier quantitative trading firms, leading AI research labs, and Big Tech. Backed by tier-one venture capital, they ship fast, maintain exceptionally high technical standards, and operate as an in-office team in London.
They are hiring a Senior Research Engineer to build and deploy core AI models from conception through production. You will work on genuinely hard, unsolved problems: building LLMs that reason reliably across long contexts, maintain coherent state over extended interactions, and make sound decisions under uncertainty – all whilst serving millions of requests with strict latency requirements.
- Novel post-training methods – Training approaches optimised for real-world task completion, not benchmarks
- Real-time evaluation and orchestration – Systems that monitor quality and adaptively route between models in production
- Long-horizon task decomposition – AI systems that autonomously break down and execute multi-step problems
Requirements:
- 5+ years AI/ML engineering or research experience with production systems
- Hands-on post-training experience (RLHF, DPO, or similar) and deployed LLMs in production
- Strong Python and modern ML tooling (PyTorch/JAX, training infrastructure, evaluation pipelines)
- Track record shipping research from prototype to production impact
- Comfortable owning work end-to-end: architecture to data pipelines to production integration
Work on genuine research problems that ship to production within weeks. Collaborate with exceptional engineers from elite quant firms, frontier AI labs, and top tech companies. Own multi-quarter initiatives and shape the research roadmap. In-office in London with some of Europe’s best AI talent.
For more information, or a discreet chat regarding the market/similar roles, please get in touch:
Research and Technology Engineer in London employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research and Technology Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech scene, especially those who work at startups. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on that perfect role.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AI/ML. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach complex problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Research and Technology Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Research Engineer. Highlight your experience with AI/ML engineering, especially any hands-on post-training work you've done. We want to see how your skills align with the challenges mentioned in the job description.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about solving complex problems in production AI systems. Share specific examples of your past work that relate to the tasks outlined in the job description. We love a good story!
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's deploying LLMs or developing novel training methods, we want to see what you've accomplished. Include links to your GitHub or any publications if you have them!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values.
How to prepare for a job interview at Durlston Partners
✨Know Your Stuff
Make sure you brush up on your AI and ML knowledge, especially around production systems and large language models. Be ready to discuss your hands-on experience with post-training methods like RLHF or DPO, as well as any projects where you've taken research from prototype to production.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some genuine research problems during the interview. Think about how you would approach complex, multi-step reasoning tasks and be ready to share examples of how you've successfully navigated similar challenges in the past.
✨Familiarise Yourself with Their Tech Stack
Since the role requires strong Python skills and familiarity with tools like PyTorch or JAX, make sure you're comfortable discussing these technologies. You might even want to bring a small project or code snippet to demonstrate your proficiency.
✨Be Ready to Collaborate
This role involves working closely with a talented team, so be prepared to discuss how you collaborate with others. Share examples of how you've contributed to team initiatives and shaped research roadmaps in previous roles.
